Thoughts on Social Machine Learning

iRobot believes that next-generation practical robots have the potential to help caregivers perform critical work and extend the time that people can live independently. Robots may be capable of assisting in senior care in a variety of real-life situations, including household chores and the on-time administration of medication. This could ultimately lower the cost for care.

I’m often asked to define what a social robot is. And the definition that I’ve been using for the past few years is “any robot that is designed to interact with people as part of its functional goal.” I like this definition because it lets the end scenario determine whether or not a robot is social rather than the designer of the robot. For example, a robot could be designed to deliver medicine to a person without very much attention to HRI, focusing only on navigation and planning, but I would still call this a social robot (albeit not likely to be a successful one).

So in this definition the Roomba is not really a social robot. When functioning properly, you shouldn’t have to interact with it very much at all. Ideally it’s mostly functioning when you are away. This move into healthcare robotics now sends iRobot squarely into the domain of social robots, designed to interact with humans as part of their functional goal. It will be exciting to see this develop!